Power Bi Full Course 2025 | Power Bi Tutorial for Beginners | Power Bi Training | Simplilearn

The video introduces PowerBI as a powerful tool for organizations to make informed decisions and opens up lucrative career opportunities for data analysts and business intelligence professionals. It covers topics like data visualization, modeling, and report creation, empowering users to excel in high-demand roles.

The video presents a practical case study where a store owner uses PowerBI to analyze sales data, identify demand patterns, forecast sales, and make informed business decisions. The store owner achieved higher profits and improved decision-making using PowerBI features like Power View and map visualizations.

The concept of business intelligence (BI) is explained as the process of collecting, analyzing, and transforming raw data into actionable insights for business purposes. The steps involved in BI, such as data processing, integration, analysis, and decision-making, are discussed to highlight the importance of BI in driving strategic decisions and improving operational efficiency.

A brief overview of top business intelligence tools like PowerBI, Tableau, and ClickView is provided, emphasizing their features and benefits for data visualization, collaboration, and real-time analytics. The video showcases how these tools empower organizations to gain a competitive edge and drive informed decision-making.

A detailed demonstration on how to create reports and dashboards in PowerBI is presented. The tutorial covers importing data from various sources, shaping and transforming data, building visualizations like matrices, bar charts, maps, donut charts, and tree maps, and customizing report layouts for effective data representation.

The process of connecting different data sources to PowerBI, including web pages, Excel sheets, CSV files, SQL databases, and PDFs, is illustrated. The video highlights the flexibility of PowerBI in importing and shaping data from diverse sources for data analysis and visualization.

Key benefits of using PowerBI for enterprise data visualization, advanced data analysis, integration with data services, seamless analytics, and secure report publishing are highlighted. PowerBI enables organizations to extract insights, streamline operations, and enhance decision-making processes.

Explains how to access PowerBI on the Microsoft website, sign up for a trial account, and install the PowerBI app on your machine.

Details the process of connecting PowerBI to different data sources, exploring data visualization options, using Power Query Editor for data transformation, and creating relationships between different data sets.

Discusses the use of data models in PowerBI, creating relationships between tables, and utilizing DAX formulas for data analysis and calculations.

Demonstrates how to publish and share reports on PowerBI, including creating, formatting, and saving reports, as well as viewing and sharing them with others.

Walks through the process of data transformation in PowerBI, filtering data, applying transformations, and loading multiple data sets for analysis and reporting.

In this section, the speaker explores the order column and demonstrates how to look for more data related to products and copiers. They explain how to filter data based on specific criteria like copiers and laser, set quantity limits for sales, and apply filters to customize the view of the data.

The speaker showcases the transformation of the product ID by splitting it based on different criteria such as country name, year, and order ID. They explain the process step by step, including creating a copy of a column, splitting it into multiple columns, and renaming the columns for better clarity.

Here, the speaker demonstrates how to group and sum data based on different categories like shipping and sales. They explain the process of creating new columns for grouping data based on specific parameters like shipping mode and segment, and show how to perform summing for sales data to extract meaningful insights.

The speaker covers the process of importing data from different sources such as web, text files, CSV files, Excel sheets, PDFs, MySQL, and SQL Server. They demonstrate how to establish connections, preview data, and load data sets into Power BI for further analysis and visualization.

In this chapter, the speaker discusses data modeling concepts such as cardinality and types of data modeling like dimensional modeling and relational modeling. They explain the importance of creating relationships between different data sets for effective reporting and visualization in Power BI.

Explained the four types of cardinalities: many-to-one, one-to-one, one-to-many, and many-to-many relationships in data modeling.

Demonstrated the process of importing master dimensions like customer data and product data into PowerBI for analysis.

Discussed the concept of creating relationships between tables and visualizing the relationships in PowerBI.

Showed how to create conditional columns based on certain criteria like product color, discount, order status, and more.

Performed calculations to determine revenue, profit, cost, and pricing based on the data in the sales table.

Derived customer insights by calculating customer age, full name, target customers, and other demographic information based on customer data.

Demonstrated manipulations on date columns such as calculating expiry dates, day names, years in between, last date of the month, and start of the month.

Introduction to calculated columns and understanding the utility of Dax functions in PowerBI for data analysis expressions and creating new measures or columns.

Exploring the basic syntax of Dax expressions to calculate totals, add new columns, and use various functions in PowerBI for data analysis.

Understanding the use of Dax functions for performing calculations, working with parent-child relationships, and creating new columns or measures in PowerBI.

Creating interactive dashboards in PowerBI by importing data, visualizing sales data, analyzing regions, categories, and managing visualizations for insights.

Explaining the importance of data cleaning in Excel, ensuring data accuracy, handling blank rows, maintaining data types, and segregating data for effective analysis.

Utilizing Chat GPT AI for data cleaning, identifying duplicates, manipulating data, and preparing data for processing in Excel.

Learn how to identify and eliminate duplicates in Excel, create pivot tables, and analyze sales performance by region.

Explore building a forecasting model in Excel to predict future sales based on historical data.

Understand the process of data cleaning and transformation using PowerBI, including loading and transforming data from Excel files.

Learn about data modeling concepts in PowerBI, including the star schema and uniting disparate data sets for analysis.

Understand the concept of a star schema in PowerBI, which organizes data into a star-shaped structure for analysis.

Discover how to use Microsoft Power Query to clean and transform data from various sources for analysis.

Learn about the importance of exploratory data analysis in identifying patterns, outliers, and relationships in data.

The speaker discusses the installation of necessary libraries like NumPy, Pandas, Seaborn, Matplotlib, and others for data analysis.

The speaker imports essential libraries like warnings, pandas, Seaborn, and Matplotlib for data manipulation and visualization in Jupyter Notebook.

The speaker imports libraries like SimpleImputer, KFold, and LightGBM for data modeling and evaluation in Jupyter Notebook.

The speaker imports student data into a data frame, checks for duplicates and null values, and uses HTML codes for visual data representation.

The speaker creates visualizations using data columns like attendance, previous exams, and other parameters to analyze relationships and patterns in the data.

The speaker categorizes data based on exam scores into different classes like first class, second class, and pass, analyzing the distribution of scores.

The speaker cleans the data, sets a threshold score, and describes the dataset to prepare it for modeling and analysis.

The speaker eliminates null values in the dataset using DataFrame cleaning techniques and ensures data quality for further analysis.

The speaker analyzes numerical values in the data, adds HTML codes for visualization, and utilizes CBOE libraries for creating visual representations of the data.

The speaker calculates the correlation matrix for selected columns and creates visualizations to analyze relationships between variables in the dataset.

Explanation on how to analyze trends and answer specific questions using PowerBI. Includes steps like choosing the report, creating multiple charts, graphs, and integrating them into the dashboard.

Guidance on handling missing data in PowerBI for both freshers and experienced candidates. Discusses approaches such as filtering values with aggregate values, using custom logic, and creating a tax formula to address missing values.

Overview of data flows in PowerBI as cloud-based preparation and management tools designed to simplify data integration and storage across various sources.

Explanation on how to handle data updates in PowerBI, including scheduled refreshes, realtime streaming data sets, and configuring schedule refreshes in PowerBI servers.

Definition and explanation of a slicer in PowerBI as a visualization tool used to filter data dynamically, providing users with the ability to select specific data for display.